Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting
M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational Research 258 (2017) 295–306.
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Journal Article
| English
Author
Bräuning, M.;
Hüllermeier, EykeLibreCat;
Keller, T.;
Glaum, M.
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Publishing Year
Journal Title
European Journal of Operational Research
Volume
258
Issue
1
Page
295-306
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Bräuning M, Hüllermeier E, Keller T, Glaum M. Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting. European Journal of Operational Research. 2017;258(1):295-306.
Bräuning, M., Hüllermeier, E., Keller, T., & Glaum, M. (2017). Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting. European Journal of Operational Research, 258(1), 295–306.
@article{Bräuning_Hüllermeier_Keller_Glaum_2017, title={Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting}, volume={258}, number={1}, journal={European Journal of Operational Research}, author={Bräuning, M. and Hüllermeier, Eyke and Keller, T. and Glaum, M.}, year={2017}, pages={295–306} }
Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application in Accounting.” European Journal of Operational Research 258, no. 1 (2017): 295–306.
M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, “Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting,” European Journal of Operational Research, vol. 258, no. 1, pp. 295–306, 2017.
Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application in Accounting.” European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.
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